Abstract
Active Queue Management (AQM) is recommended by Internet Engineering Task Force to mitigate the bufferbloat phenomenon in the Internet. In this paper, we show the results of comprehensive measurements carried out in our university network, in which a device with an AQM algorithm, designed and programmed for this purpose, was running. The implemented AQM algorithm was based on the dropping function, i.e. arriving packets were dropped randomly, with the probability being a function of the queue length. Several different dropping function forms, proposed in the networking literature, were used, in addition to the classic FIFO queue (no AQM). The experiment lasted over a month, during which the state of the network was measured and recorded several thousand times. This made the results independent of the natural fluctuations of the users’ behavior and the network load. Conclusions on the general performance improvement offered by the implemented AQM, as well as the differences in the performance between particular forms of the dropping function, were reached. Some of these conclusions differ from those drawn previously from simulations. This underlines the need for carrying measurements of new AQMs in real, operating networks, with complex, natural traffic.
Highlights
In the early Internet, the buffers at network devices were meant to mitigate the losses caused by the statistical multiplexing of flows incoming from different directions
We show the results of comprehensive measurements carried out in our university network, in which a device with an Active Queue Management (AQM) algorithm, designed and programmed for this purpose, was running
We presented the results of an experiment carried out in our university network, in which an AQM device, designed and programmed for this experiment, was running
Summary
In the early Internet, the buffers at network devices were meant to mitigate the losses caused by the statistical multiplexing of flows incoming from different directions. Each measurement lasted as long as 2 million packets passed through the AQM device During such period, several performance characteristics were recorded, including the network load, the average queue size and its standard deviation, the packet loss ratio and the packet burst ratio. [24, 28,29,30] Some of these theoretical results have been used to parameterize the dropping functions, implemented in the AQM device to provide a specific performance goal, i.e. the average queue size of 50 packets at the network load of 1. Five graphs depicting the mean queue length, its standard deviation, the loss ratio, the burst ratio and the total impairment factor, for different loads and dropping functions, are AQM based on the queue length: A real-network study presented and discussed. It reflects the stability of the queue size, provided by the AQM mechanism and influences the delay jitter of the transmission
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